Poverty maps, spatial descriptions of the distribution of poverty in any given country, are most useful to policy-makers and researchers when they are finely disaggregated, i.e. when they represent small geographic units, such as cities, towns, or villages. Unfortunately, almost all household surveys are too small to be representative at such levels of disaggregation, and most census data do not contain the required information to calculate poverty.

The 1996 South African census is an exception, in that it does contain income information for each individual in the household. In this paper, we show that the income from the census data provides only a weak proxy for the average income or poverty rates at either the provincial level or at lower levels of aggregation. We also demonstrate a simple method of imputing expenditures for every household in the census, using information in the October Household Survey (OHS) and the Income Expenditure Survey (IES) in 1995. The resulting predicted household consumption values are plausible and provide a good fit with the IES data.

We also provide an example, which demonstrates that poverty headcount can be imputed with fair precision for Magisterial Districts and for Transitional Local Councils. Finally, our paper serves as a reminder of the value of comparing various data sources for external validation and it underlines the need to make more use of census data that seems to be underutilized in most developing countries.